Using Metabolomics to Optimize Bioprocessing

Bioprocessing Studies

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Figure 2. Overview of a typical metabolomics experiment for bioprocessing

It is estimated that the number of biochemicals and metabolites in a cell is on the order of several thousand. For media-optimization studies, only a handful of biochemical markers are analyzed (e.g., glucose, lactate, acetate, glutamate, glutamine, ammonia). For some situations, these markers may not be relevant to the phenotype, and additional biochemical and metabolic measurements will increase insight into optimization.

Applying metabolomics to bioprocessing involves measuring the biochemicals and metabolites from both the media and from within the cells. An overview of a typical metabolomics experiment for bioprocessing utilizing Metabolon’s analytical platform is shown in Figure 2.

The experiment begins with the collection of samples from a shake flask or bioreactor over time of interest. For CHO cell experiments, for example, this can include sampling each day over a 14-day period. The cells are separated from spent media and flash frozen. Each sample is extracted to isolate the biochemicals and metabolites (typically <1,500 MW) and divided into three portions. Each aliquot is analyzed using a different analytical platform: two UHPLC-MS/MS ESI platforms (positive ESI and negative ESI) and one GS-MS platform.

The software processes the mass spectral data, detecting and integrating chromatographic peaks. Each peak is composed of a number of mass spectra (nominal mass and MS/MS fragmentation pattern). By comparing the retention time of the peak and the mass spectral information to a database of biochemical standards, the software can rapidly identify hundreds of analytes in a single sample.

Then the data is statistically analyzed to determine significant changes at each time point compared to the baseline sample. These metabolic changes are grouped by pathway and color-coded to allow rapid determination of pathways altered. Because both cells and spent media are analyzed, changes in the media can be compared to changes in cellular metabolism. This allows researchers to monitor the impact of biochemicals depleted in the media and their impact on the metabolism of the cell. Likewise, accumulation of toxic metabolites and their effect can be determined.

Metabolomics technology can be applied to bioprocessing operations in two ways. The first application is in finding targets for metabolic engineering, formulating growth media, and identifying areas for potential process improvement. For example, metabolomics can uncover novel metabolism, find blind spots in media requirements, and help to develop feeding strategies. The knowledge gained can also generate hypotheses for further testing.

The other general application for metabolomics is biomarker discovery. By using the rich global information from this analysis, new markers can be discovered. These new markers can be employed at any point in cell culture development work, much like the way lactate or ammonia are currently used. This may include selection criteria for clone selection or media development, process development monitoring and other potential downstream uses (CQA for PAT and QbD).